Security assessment of a turbine generator using H/sup infinity / control based on artificial neural networks and expert systems

E. Nascimento, P. Goswami, E. Kasenally, B. Cory, D. Macdonald
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引用次数: 1

Abstract

The authors describe a preliminary framework for real time security assessment of turbine generators that integrates artificial neural networks (ANN) and knowledge-based expert systems (KBES). The authors also present the transient stability assessment of a turbine generator using a back propagation artificial neural network. Additional signals have been added to the AVR and governor loops of the turbine generator using H/sup infinity / control. The ANN's ability to learn, interpolate and reproduce behaviour is presented, showing how the stability of a high order nonlinear system can be obtained without the prior solution of the state equations.<>
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基于人工神经网络和专家系统的H/sup∞/控制汽轮发电机安全评估
提出了一种基于人工神经网络(ANN)和基于知识的专家系统(KBES)的汽轮发电机实时安全评估框架。本文还提出了利用反向传播人工神经网络对汽轮发电机进行暂态稳定评估的方法。额外的信号已添加到AVR和调速器循环的涡轮发电机使用H/sup无限/控制。介绍了人工神经网络的学习、插值和再现行为的能力,展示了如何在不需要状态方程的先验解的情况下获得高阶非线性系统的稳定性
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